Cross-comparison of patient-derived xenografts and derivative organoids and cell lines for translational research in hepatocellular carcinoma

患者来源的异种移植物和衍生类器官和细胞系的交叉比较，用于肝细胞癌的转化研究

• 批准号: 10041707
• 负责人: David E Kaplan
• 金额: --
• 依托单位: PHILADELPHIA VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10041707
• 关键词: Achievement; Address; BAY 54-9085; Biological; Biological Assay; Biology; Biopsy; Biopsy Specimen; Cancer Etiology; Cell Line; Cells; Cessation of life; Chemoresistance; Complex; Credentialing; Diagnosis; Disease; Engraftment; Evaluation; Excision; Generations; Heterogeneity; Human; Image; Life Expectancy; Malignant Neoplasms; Methodology; Modeling; Mutation; Operative Surgical Procedures; Organoids; Outcome; Parents; Patients; Pharmaceutical Preparations; Pharmacotherapy; Polymerase Chain Reaction; Population; Pre-Clinical Model; Prediction of Response to Therapy; Primary carcinoma of the liver cells; Prognosis; Reporting; Resected; Role; Sampling; Source; Specimen; Testing; Therapeutic; Tissues; Translational Research; Transplantation; Tumor-Derived; Unresectable; Validation; Work; advanced disease; cell free DNA; clinically relevant; design; digital; improved; interest; novel; patient derived xenograft model; patient response; predictive modeling; response; targeted sequencing; targeted treatment; therapy development; translational model; tumor; tumor heterogeneity

PROJECT SUMMARY Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide with more than 745,000 fatalities in 2012 alone. The majority of patients with HCC present with unresectable disease at diagnosis and a life expectancy of less than 20 months, with only 15% of these patients surviving more than one year after diagnosis. This dismal prognosis underscores the limited therapeutic options for these patients. HCC is a notoriously chemoresistant malignancy and advances in targeted therapeutics have been unsuccessful in improving survival resulting in what some have called “a losing battle” in the development of therapies. This deficiency issues, in large part, from limitations of current preclinical models in (i) recapitulating the inter- and intra-tumoral heterogeneity that characterizes HCC and (ii) predicting patient response to therapeutics. While patient-derived tumor models have been demonstrated to more faithfully recapitulate the heterogeneity of human tumors, there has been limited validation of the translational relevance of these models with respect to their fidelity to the intra- and inter-tumoral mutational heterogeneity that characterizes HCC as well as their ability to provide translationally reliable information for the design, testing and/or outcome evaluation of novel or existing therapies. Indeed, the creation of new patient-derived models of HCC requires rigorous validation of the resulting tumors to confirm their fidelity to the cancer of interest and robust credentialing criteria to ascertain their biological relevance and reliability as surrogates of patient response. In preliminary studies we have: 1) demonstrated the ability to generate PDXs and PDX-derived cell lines from percutaneous biopsies of tumors in patients with intermediate stage HCC and 2) developed methodologies to enable the characterization, validation and optimization of these models. The proposed project will build on this prior work to assess the fidelity and predictive potential of patient-derived models of HCC. We hypothesize that patient-derived models of HCC derived from percutaneous biopsies recapitulate the inter- and intra-tumoral heterogeneity of their parent biopsies and that these models are predictive of patient response to therapy. To test this hypothesis the proposed project will pursue three aims: (1) to define the representation of inter- and intra-tumoral clonal heterogeneity of patient-derived models of HCC through targeted sequencing and digital polymerase chain reaction; (2) to determine the predictive potential of patient-derived models of HCC for response to common HCC therapies; and (3) to investigate the role of HCC tumor initiating cells (TICs) in improving the yield and predictive potential of patient-derived models of HCC. Importantly, the achievement of the proposed aims will transform the utility of patient-derived models of HCC for translational research.

项目摘要 肝细胞癌（HCC）是全球范围内癌症相关死亡的第二大原因， 仅2012年就有74.5万人死亡。大多数HCC患者在手术后出现不可切除的疾病， 诊断和预期寿命不到20个月，只有15%的患者存活超过一个月。 诊断后一年。这种令人沮丧的预后强调了这些患者的治疗选择有限。HCC 是一种众所周知的化疗耐药性恶性肿瘤，靶向治疗的进展一直不成功， 提高生存率，导致一些人称之为治疗发展中的“失败之战”。这 缺陷问题，在很大程度上，从目前的临床前模型的局限性，在（i）概括间， 表征HCC的肿瘤内异质性和（ii）预测患者对治疗剂的反应。 虽然患者来源的肿瘤模型已被证明更忠实地概括了肿瘤的异质性， 在人类肿瘤中，这些模型的翻译相关性的验证有限， 它们对HCC特征性的肿瘤内和肿瘤间突变异质性的保真度以及它们的能力， 为新的或现有的药物的设计、测试和/或结果评价提供可靠的信息。 治疗事实上，新的HCC患者衍生模型的创建需要对所得到的结果进行严格的验证。 和稳健的认证标准以确定其生物学特性。 相关性和可靠性作为患者反应的替代品。 在初步研究中，我们已经：1）证明了从细胞中产生PDX和PDX衍生的细胞系的能力。 中期HCC患者的经皮肿瘤活检和2）开发方法， 能够对这些模型进行表征、验证和优化。拟议项目将以此为基础 以前的工作，以评估保真度和预测潜力的病人来源的模型肝癌。 我们假设来自经皮活检的患者HCC模型概括了 和肿瘤内异质性，并且这些模型可预测患者反应 接受治疗为了验证这一假设，拟议的项目将追求三个目标：（1）定义代表性 通过靶向测序分析HCC患者模型的肿瘤间和肿瘤内克隆异质性 和数字聚合酶链反应;（2）确定患者来源的HCC模型的预测潜力 对常见HCC疗法的反应;和（3）研究HCC肿瘤起始细胞（TIC）在 提高HCC患者衍生模型的产量和预测潜力。重要的是，实现 所提出的目标将改变用于转化研究的患者来源的HCC模型的效用。